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      Rhizosphere soil microbial community and its response to different utilization patterns in the semi-arid alpine grassland of northern Tibet

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          Abstract

          As the link between plants and soils, rhizosphere soil microorganisms play an important role in the element cycle. This study aimed to understand the response of the rhizosphere soil microbial community structure and interaction network to grassland utilization in the alpine steppe of the northern Tibet Plateau. High-throughput sequencing was employed to study the composition, diversity, and species interaction network of rhizosphere soil microbial communities under grazing, mowing, and enclosing treatments. Proteobacteria (47.19%) and Actinobacteria (42.20%) were the dominant bacteria in the rhizosphere soil. There was no significant difference in relative abundance among rhizosphere soil microorganisms at phylum and genus levels, but differences were found in Chlorobi, Ignavibacteriae, and Micromonospora. The alpha diversity index based on Shannon, Chao1, and Simpson indices revealed that except for a significant difference in the Shannon index of the Artemisia nanschanica group, the richness and evenness of rhizosphere soil microbial communities among all groups were similar. Non-metric multidimensional scaling (NMDS) and multi-response permutation procedure (MRPP) analyses showed that the inter-group differences of three plants ( Stipa purpurea, Carex moorcroftii, and Artemisia nanschanica) were greater than the differences within the groups; however, only the inter-group difference with the Stipa purpurea group was significant. The microbial interaction network showed that the network complexity of the Artemisia nanschanica group and the enclosing treatment, which were not easily influenced by external factors, were higher than those of the other groups and treatments; this again demonstrated that Proteobacteria and Actinobacteria were the network core microbial species in alpine steppe of the northern Tibet Plateau and were crucial for maintaining stability of the microbial communities. Findings from this study provide a theoretical basis for the restoration of degraded alpine grassland and the development of microbial functions.

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            QIIME allows analysis of high-throughput community sequencing data.

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              CD-HIT: accelerated for clustering the next-generation sequencing data

              Summary: CD-HIT is a widely used program for clustering biological sequences to reduce sequence redundancy and improve the performance of other sequence analyses. In response to the rapid increase in the amount of sequencing data produced by the next-generation sequencing technologies, we have developed a new CD-HIT program accelerated with a novel parallelization strategy and some other techniques to allow efficient clustering of such datasets. Our tests demonstrated very good speedup derived from the parallelization for up to ∼24 cores and a quasi-linear speedup for up to ∼8 cores. The enhanced CD-HIT is capable of handling very large datasets in much shorter time than previous versions. Availability: http://cd-hit.org. Contact: liwz@sdsc.edu Supplementary information: Supplementary data are available at Bioinformatics online.
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                Author and article information

                Contributors
                Journal
                Front Microbiol
                Front Microbiol
                Front. Microbiol.
                Frontiers in Microbiology
                Frontiers Media S.A.
                1664-302X
                22 July 2022
                2022
                : 13
                : 931795
                Affiliations
                [1] 1Key Laboratory of Mountain Surface Processes and Ecological Regulation, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences , Chengdu, China
                [2] 2Chinese Academy of Sciences, University of the Chinese Academy of Sciences , Beijing, China
                Author notes

                Edited by: Gang Yang, Southwest University of Science and Technology, China

                Reviewed by: Jinsong Wang, Institute of Geographic Sciences and Natural Resources Research (CAS), China; Dandan Izabel-Shen, Stockholm University, Sweden; Wentao Luo, University of Chinese Academy of Sciences, China

                *Correspondence: Yan Yan yy@ 123456imde.ac.cn

                This article was submitted to Extreme Microbiology, a section of the journal Frontiers in Microbiology

                Article
                10.3389/fmicb.2022.931795
                9354816
                35935214
                bba9258f-cea5-4884-81c0-300bdd709544
                Copyright © 2022 Fu, Yan, Li, Liu and Lu.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 29 April 2022
                : 27 June 2022
                Page count
                Figures: 8, Tables: 4, Equations: 3, References: 79, Pages: 0, Words: 9531
                Funding
                Funded by: National Natural Science Foundation of China, doi 10.13039/501100001809;
                Award ID: 41871049
                Award ID: 41877338
                Categories
                Microbiology
                Original Research

                Microbiology & Virology
                rhizosphere soil microorganisms,community structure,diversity,interaction network,dnbseq sequencing,alpine steppe

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